Poly(ADP-ribose) polymerases (PARP) are a family of enzymes involved with multiple facets of cellular function including DNA damage repair (DDR) and chromatin stability, along with others that are just being discovered. The importance of PARP in DDR, specifically non-homologous end joining, makes it an ideal therapeutic target in cancer where DDR deficiencies are prominent. Clinical targeting of PARP was first performed in patients harboring BRCA mutations, and thus defects in homologous recombination, where PARP inhibition is synthetically lethal. Although effective, PARP inhibitors (PARPi) did not prove as ground breaking as hoped due to several resistance mechanisms and the complexity of DDR. Currently there are 3 approved PARP inhibitors for treatment of patient with ovarian cancer and two more in late stage clinical trials. However, our understanding of molecular biology underlying PARP efficacy remains limited. Intriguingly, knocking out PARP does not produce the cellular lethality found with PARP inhibitor, which was recently explained by the discovery that PARP inhibitors trap PARP to sites of DNA damage. However, even though they bind into the same protein pocket and have similar affinities, some PARP inhibitors are much more potent trappers, the reason remains unknown. Thus, PARP inhibitors function through both trapping and and enzymatic inhibition. Our preliminary analysis of cell line response databases demonstrates wide differences in cell line susceptibility to different PARP inhibitors, with some cell lines more sensitive to low trapping inhibitors and other more sensitive to high trapping inhibitors. Determining the mechanisms of differential PARP inhibitor sensitivity would provide insight into clinical selection among the PARP inhibitors to drive more effective therapies. Here we will address three specific aims through novel approaches of single cell protein expression and dynamics: 1) determine PARPi- specific drivers of cellular response to select optimal PARPi treatment, 2) elucidate the molecular mechanism of PARPi sensitivity to optimize combination therapy, and 3) optimally pair PARPi to increase efficacy and minimize toxicity. Resolving the mechanisms of PARP inhibitor efficacy will enable optimal clinical use and combination trial design. We expect to determine biomarkers of response for each of the clinical PARP inhibitors that will guide clinical selection of PARPi treatment.